ANALYSIS OF ECONOMIC LOAD DISPATCH USING FUZZIFIED PSO

Abstract

With large interconnection of the electric networks, the energy crisis in the world and continuous rise in prices, it is very essential to reduce the running charges of the electric energy i.e., reduce the fuel consumption for meeting a particular load demand. The main aim in the economic dispatch is to minimize the total cost of generating real power at various stations while satisfying the loads and the losses in transmission links. A novel method is introduced in the planning and operation of power systems to provide reliable and quality power to consumers at economical cost. The primary objective of this paper is to develop efficient and fast Fuzzified Particle Swarm Optimization (FPSO) algorithm that can be applied to obtain the optimal solutions of multi-constrained dynamic ED, OPF. In this paper, I considered Fuzzified particle swam optimization to solve multi-constrained dynamic economic dispatch problem. The FPSO Method is inferred to have superior features than conventional methods and gives faster and stable convergence characteristics. PSO is popular due to its significant property of dealing with optimization problem and ease of computation. But the critical drawback of PSO is more number of iterations required and hence the computation time is required to obtain the optimal solution is more and also the premature convergence Hence to overcome the premature convergence and to speed up the process, a classical PSO technique is incorporated with fuzzy logic to get a faster convergence This improved technique is termed as Fuzzified Particle Swarm Optimization (FPSO). The proposed method can provide an accurate solution with fast convergence and has the potential to be applied to other power system optimization problems.